Instructions to use Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF

SGLang

How to use Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF with Docker Model Runner:
```
docker model run hf.co/Jackrong/Qwopus3.6-35B-A3B-v1-MTP-GGUF
```

LFM

by cybertruck32489 - opened Jul 11

Discussion

cybertruck32489

Jul 11

Can u pls fine tune https://huggingface.co/LiquidAI/LFM2.5-8B-A1B with opus/fable datasets?

Jackrong

Owner Jul 14

Hi! Thanks for the support and the great suggestion.

However, after looking into it, the LiquidAI LFM series utilizes a non-Transformer, structured state-space/linear time-varying architecture, which is fundamentally different from the traditional self-attention mechanism used in Qwen models.

Due to these significant differences in the underlying mathematical principles and architecture, fine-tuning LFM models requires a completely different approach, and it poses quite a few practical challenges at the moment.

Thanks again for the idea, though! I really appreciate your interest.

cybertruck32489

Jul 14

Hi. Thanks for your reply. As far as I know, they have documentation on their website, as well as a Discord channel where you can get help. As far as I know, they’re trained exactly the same way as regular Transformers. This model is supported by Unsloth, for example.

ArcheyChen

Jul 16

https://github.com/s-JoL/open-reasoning

Check this! It can decrypt the claude COT！！！

Qwfable pls！！！！！

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